| 000 | 04146nam a22006015i 4500 | ||
|---|---|---|---|
| 001 | 978-3-031-19845-8 | ||
| 003 | DE-He213 | ||
| 005 | 20260304124443.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 230223s2023 sz | s |||| 0|eng d | ||
| 020 |
_a9783031198458 _9978-3-031-19845-8 |
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| 024 | 7 |
_a10.1007/978-3-031-19845-8 _2doi |
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| 050 | 4 | _aTA703-705.4 | |
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_aRB _2bicssc |
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_a624.151 _223 |
| 245 | 1 | 0 |
_aGeostatistics Toronto 2021 _h[electronic resource] : _bQuantitative Geology and Geostatistics / _cedited by Sebastian Alejandro Avalos Sotomayor, Julian M. Ortiz, R. Mohan Srivastava. |
| 250 | _a1st ed. 2023. | ||
| 264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2023. |
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| 300 |
_aXVII, 281 p. 146 illus., 129 illus. in color. _bonline resource. |
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| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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| 347 |
_atext file _bPDF _2rda |
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| 490 | 1 |
_aSpringer Proceedings in Earth and Environmental Sciences, _x2524-3438 |
|
| 505 | 0 | _aA Geostatistical Heterogeneity Metric For Spatial Feature Engineering -- Iterative Gaussianisation For Multivariate Transformation -- Comparing And Detecting Stationarity And Dataset Shift -- Simulation Of Stationary Gaussian Random Fields With A Gneiting Spatio-Temporal Covariance -- Spectral Simulation Of Gaussian Vector Random Fields On The Sphere -- Geometric And Geostatistical Modeling Of Point Bars -- Application Of Reinforcement Learning For Well Location Optimization -- Compression-Based Modelling Honouring Facies Connectivity In Diverse Geological Systems -- Spatial Uncertainty In Pore Pressure Models At The Brazilian Continental Margin -- The Suitability Of Different Training Images For Producing Low Connectivity, High Net:Gross Pixel-Based Mps Models -- Probabilistic Integration Of Geomechanical And Geostatistical Inferences For Mapping Natural Fracture Networks. | |
| 506 | 0 | _aOpen Access | |
| 520 | _aThis open access book provides state-of-the-art theory and application in geostatistics. Geostatistics Toronto 2021 includes 28 short abstracts, 18 extended abstracts, and 7 full articles in the fields of geostatistical theory, multi-point statistics, earth sciences, mining, optimal drilling, domains, seismic, classification uncertainty risk, and artificial intelligence and machine learning. All contributions were presented at the 11th International Geostatistics Congress held in virtually at Toronto, Canada, from July 12-16, 2021. This book is valuable to researchers, scientists, and practitioners in geology, mining, petroleum, geometallurgy, mathematics, and statistics. | ||
| 650 | 0 | _aGeotechnical engineering. | |
| 650 | 0 |
_aStatistics . _9905 |
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| 650 | 0 | _aGeophysics. | |
| 650 | 1 | 4 | _aGeotechnical Engineering and Applied Earth Sciences. |
| 650 | 2 | 4 |
_aApplied Statistics. _911455 |
| 650 | 2 | 4 | _aGeophysics. |
| 700 | 1 |
_aAvalos Sotomayor, Sebastian Alejandro. _eeditor. _0(orcid)0000-0002-2521-6727 _1https://orcid.org/0000-0002-2521-6727 _4edt _4http://id.loc.gov/vocabulary/relators/edt _923764 |
|
| 700 | 1 |
_aOrtiz, Julian M. _eeditor. _0(orcid)0000-0001-5187-9244 _1https://orcid.org/0000-0001-5187-9244 _4edt _4http://id.loc.gov/vocabulary/relators/edt _923765 |
|
| 700 | 1 |
_aSrivastava, R. Mohan. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _923766 |
|
| 710 | 2 | _aSpringerLink (Online service) | |
| 773 | 0 | _tSpringer Nature eBook | |
| 776 | 0 | 8 |
_iPrinted edition: _z9783031198441 |
| 776 | 0 | 8 |
_iPrinted edition: _z9783031198465 |
| 776 | 0 | 8 |
_iPrinted edition: _z9783031198472 |
| 830 | 0 |
_aSpringer Proceedings in Earth and Environmental Sciences, _x2524-3438 _923488 |
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| 856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-031-19845-8 |
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